May 1, 2024
Updated June 2, 2025
24 minute read
An In-Depth Exploration of Google Cloud Platform
Google Cloud Platform (GCP) is a suite of cloud computing services offered by Google, running on the same infrastructure that Google uses internally for its end-user products, such as Google Search, Gmail, and YouTube. It provides a series of modular cloud services including computing, data storage, data analytics, and machine learning, alongside a comprehensive set of management tools. Individuals and enterprises can leverage these services to build, deploy, and scale applications, store and analyze data, and utilize advanced technologies like artificial intelligence and machine learning. The platform is designed to be flexible, allowing users to access resources on a pay-per-use basis or sometimes for free, depending on the service and usage levels.
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Find a path to becoming a Google Cloud Platform. Learn more at:
OpenCourser.com/topic/ef9g9m/google
Reading list
We've selected 23 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Google Cloud Platform.
This study guide comprehensive resource for individuals preparing for the Professional Cloud Architect certification. It covers a broad range of architectural concepts and best practices on GCP, making it essential for those aiming for advanced roles. It includes practice questions and online learning tools.
Focused specifically on cloud security on GCP, this book is invaluable for those preparing for the Professional Cloud Security Engineer certification. It covers cloud security basics, GCP security tools, and their implementation through clear explanations and practice exercises.
Similar to the other official study guides by Dan Sullivan, this book key resource for the Professional Data Engineer certification. It covers the concepts and practices required for data engineering on GCP, including data processing, analysis, and machine learning.
An expert guide for the Professional Machine Learning Engineer certification, this book covers the entire ML process on GCP, from data and feature engineering to model training and deployment using Vertex AI, TensorFlow, and Kubeflow.
Is tailored for individuals pursuing the Professional Cloud Network Engineer certification. It covers all exam objectives and provides hands-on examples using gcloud commands, making it a practical guide for network professionals on GCP.
Aimed at the Associate Cloud Engineer certification, this book provides a solid understanding of deploying and managing applications and infrastructure on GCP. It's an excellent resource for beginners and those looking to validate their foundational GCP skills.
A practical guide focusing on operationalizing scalable data analytics systems on GCP. It covers services like BigQuery, Cloud SQL, Cloud Storage, and Dataflow with hands-on examples. is highly relevant for those interested in data engineering on GCP and preparing for the Professional Data Engineer exam.
Specifically designed for beginners, this book provides a solid foundation in GCP capabilities. It covers setting up accounts, using core services like Cloud Storage, Compute Engine, and Kubernetes Engine. It is particularly useful for those preparing for the GCP Associate Cloud Engineer certification.
Focuses on applying data science techniques on GCP, leveraging its various data services. It's a valuable resource for data scientists and analysts who want to perform data processing and analysis at scale on the platform.
Delves into building, training, and optimizing machine learning models on GCP using services like Google Cloud Machine Learning Engine and TensorFlow. It's a practical guide for data scientists and ML developers looking to leverage GCP for their projects.
Offers a hands-on introduction to Google Cloud, covering practical skills and use cases. It's suitable for newcomers to the cloud and those who prefer a practical approach to learning GCP's core concepts and services.
This guide is ideal for anyone looking to become familiar with the comprehensive list of services in GCP, including compute, storage, database, networking, and big data. It covers essential concepts and provides an overview of best practices for deploying workloads. It good starting point for beginners and cloud professionals migrating to GCP.
Explores using GCP's AI-powered services for various applications, from chatbots to image analysis. It's suitable for those with a background in math and Python who want to apply AI/ML on GCP. It provides step-by-step guidance for building and training models.
Guides the reader through building scalable applications on GCP, starting with App Engine and Compute Engine. It covers implementing authentication, security, and using Cloud APIs, making it a practical guide for developers.
Provides an excellent general overview of GCP services, covering deployment of scalable cloud applications. It's suitable for those new to GCP but with some cloud experience, offering practical insights and worked examples. It serves as a strong foundation for understanding the breadth of GCP's offerings.
Is designed as an entry point to GCP and the Cloud Digital Leader certification. It simplifies basic technological elements of GCP and is suitable for aspiring IT professionals and enthusiasts. It covers cloud fundamentals, data, AI/ML, infrastructure, and security.
Offering a collection of practical recipes, this book provides solutions to common tasks and challenges on GCP. It's a useful reference for developers and administrators needing quick, step-by-step guides for implementing various GCP services.
Offers a high-level overview of GCP services through illustrations, making complex concepts more accessible. It's a valuable resource for quickly grasping the relationships between different GCP components and is suitable for visual learners and those seeking a quick reference.
While not solely focused on GCP, this book provides a strong foundation in cloud computing principles, architecture, and security that are highly relevant to understanding any cloud platform, including GCP. It's beneficial for gaining prerequisite knowledge.
Introduces platform-agnostic cloud architecture patterns that are highly relevant to designing applications on GCP. While not specific to GCP, the patterns for scalability, handling failure, and distributed users are fundamental for building effective cloud-native applications.
A comprehensive guide to Google Cloud BigQuery, a fully managed, scalable data warehouse service.
A guide to using Google Cloud Platform for cloud computing, covering topics such as infrastructure, storage, and networking.
A practical guide to using Google Cloud Platform for data science projects.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/ef9g9m/google
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